The stakes to compete in computer related applications (Apps) and the game market are extremely high. Today end users expect that Apps are free to download. App developers have to make revenues by using other ways such as advertising or in-app purchase. The cost for an App developer to acquire a user is expensive and most of the budget is typically spent on advertising.
For developers it is essential to spend their acquisition budget on the right users. Therefore it is important to have a good profile of a potential user and to be able to detect when there is a potential opportunity to get the end user's attention.
In addition, traditional profiling of the users is very static and does not necessarily fit well with a real user behaviour or actions. For example when a user finds a new type of game, the skill level might change from experienced to beginner if the user starts to play games within a new genre. These distinctions are very essential and distributing those in real-time helps developers and advertising networks (Ad network) to make correct decisions. Hence, there is a need for improving profiling of users of Apps.
A single user may have several Apps downloaded on an electronic device, such as a smartphone, tablet, etc. and each App uses separate user profiles. This can make it a hassle for users to handle and update the profiles for the different applications.